| CNN1.py | 4 years ago | ||
| CNN2.py | 4 years ago | ||
| CNN3.py | 4 years ago | ||
| README.md | 4 years ago | ||
| VNet3D-master.iml | 4 years ago | ||
| __init__.py | 4 years ago | ||
| csv.cpython-36.pyc | 4 years ago | ||
| discriminator.py | 4 years ago | ||
| layer.py | 4 years ago | ||
| main.py | 4 years ago | ||
| misc.xml | 4 years ago | ||
| modules.xml | 4 years ago | ||
| pixel_dcn.cpython-36.pyc | 4 years ago | ||
| util.py | 4 years ago | ||
| vcs.xml | 4 years ago | ||
| workspace.xml | 4 years ago | ||
CNNs detection program is made in Python, there are 3 models in total, corresponding to “CNN1.py”, “CNN2.py” and “CNN3.py” in the project. Please run the prediction function in “main” file and choose the model for prediction. The program requires the bone segmentation result of thresholding detection program, so please set the path of data folder and run the thresholding detection program first to get bone files:
In the cross-validation experiment, the dataset is divided to 6 groups as follows: Group 1: 23, 45 Group 2: 6, 8, 35, 43 Group 3: 22, 37, 48 Group 4: 12, 20, 36, 38, 51 Group 5: 19, 3, 40, 47, 49 Group 6: 15, 17, 21, 24, 27, 29, 31, 32, 39, 41, 42, 44, 46, 53